#pipeline

Story generation pipeline skill

Story generation pipeline skill. Supports multi-episode continuous generation, graph management, AI quality check + human confirmation dual control mechanism. Automatically manages relationships between characters, scenes, and hooks.

hexidyg@hexidyg

Install

openclaw skills install @hexidyg/story-pipeline

Story Generation Pipeline Skill

Features

This skill implements a complete story generation pipeline:

Continuous Episode Generation - Automatically generates next episode based on previous content
Graph Management - Storage and querying of character, scene, and hook relationships
Dual Confirmation Control - AI quality check followed by human confirmation
State Persistence - Supports pause, resume, and multiple parallel stories

Core Workflow

text

┌──────────────┐    ┌──────────────┐    ┌──────────────┐    ┌──────────────────┐
│ Generate Ep N│ -> │ AI Review    │ -> │ Graph Storage│ -> │ Wait Human Confirm│
└──────────────┘    └──────────────┘    └──────────────┘    └──────────────────┘
       │                   │                   │                      │
       ▼                   ▼                   ▼                      ▼
  Query Graph         Pass/Retry        Store Relations        Continue/Modify/End

Usage

Start New Pipeline

text

User: Start a new story pipeline, theme: Chinese girl comeback, target episodes: 10

Continue Pipeline

text

User: Continue story pipeline [pipeline_id]

User Confirmation Actions

text

User: Approved, continue to next episode
User: Modify: [specific feedback]
User: Pause
User: End

Dual Confirmation Control Mechanism

Layer 1: AI Quality Check

After each episode is generated, AI automatically checks:

Check Item	Description
Plot Coherence	Natural connection with previous episode
Character Consistency	Character behavior matches established traits
Hook Handling	Reasonable addition/closure of hooks
Pacing Control	Appropriate plot progression speed
Emotional Curve	Reasonable emotional ups and downs

Scoring Standard: 0-10 points, below 7 triggers retry (max 3 times)

Layer 2: Human Confirmation

After AI review passes, display preview and wait for user confirmation:

text

📋 Episode N Preview
━━━━━━━━━━━━━━━━━━━━━━━━
【Plot Summary】
...

✅ AI Score: 8.5/10
✅ Hook Status: 1 new, 1 closed

Please select:
1️⃣ Approved, continue to next episode
2️⃣ Needs modification (please specify)
3️⃣ Pause
4️⃣ End
━━━━━━━━━━━━━━━━━━━━━━━━

Graph Management

Graph Query

Before generating episode N, query episode N-1's graph:

python

graph_manager.query_graph(pipeline_id, episode=N-1)

Returns:

Complete content of previous episode
Character list and their statuses
Unclosed hooks
Key scenes
Relationship network

Graph Storage

After user confirmation, store current episode's complete content:

python

graph_manager.save_graph(pipeline_id, episode=N, content)

Stores: Complete generation result of the episode (not split into elements)

State Management

State File: `data/pipeline_state.json`

json

{
  "pipelines": {
    "pipeline_2026-03-05-001": {
      "theme": "Chinese girl comeback",
      "target_episodes": 10,
      "current_episode": 3,
      "status": "waiting_user_confirm",
      "created_at": "2026-03-05T15:00:00",
      "updated_at": "2026-03-05T15:30:00",
      "ai_review": {
        "score": 8.5,
        "checks": {...}
      },
      "last_output": {
        "episode": 3,
        "summary": "...",
        "content": "Complete content..."
      }
    }
  }
}

Status Types

Status	Description
`generating`	Currently generating
`ai_reviewing`	AI review in progress
`waiting_user_confirm`	Waiting for human confirmation
`paused`	Paused
`completed`	Completed
`error`	Error state

Script Description

pipeline.py - Main Control Loop

Initialize pipeline
Coordinate modules
Handle user commands
Manage loop state

ai_reviewer.py - AI Quality Check

Execute quality scoring
Generate review report
Determine pass/fail

episode_generator.py - Episode Generation

Generate new episode based on graph context
Handle hook continuation and closure
Handle retry logic

graph_manager.py - Graph Management

Graph query (call remote API)
Graph storage (call remote API)
Local cache management

API Description

Graph API

Query API:

json

{
  "action": "query",
  "pipeline_id": "pipeline_2026-03-05-001",
  "episode": 2
}

Storage API:

json

{
  "action": "save",
  "pipeline_id": "pipeline_2026-03-05-001",
  "episode": 3,
  "content": "Complete generation content for episode 3..."
}

Episode Generation Logic

First Episode Generation

Based on user-provided theme and goals, generate:

Main character settings
Initial scenes
Core conflict
Open hooks

Subsequent Episode Generation

Based on graph query results:

Read previous episode content and unclosed hooks
Continue main plot line
Handle hooks (continue/close/add)
Advance character growth arc
Adjust emotional curve

Finale Generation

When target episodes reached or user requests end:

Close all remaining hooks
Complete character growth arcs
Generate conclusive ending

Important Notes

Retry Mechanism - Max 3 retries when AI review fails
Pause/Resume - Can resume via pipeline_id after pause
Multiple Pipelines - Supports running multiple different-themed pipelines simultaneously
Graph Consistency - Ensure correct character and hook relationships
Hook Management - Track creation and closure status of each hook

Complete Workflow

Step 1: Create Pipeline

text

User: Start a new pipeline, theme: Cultivation boy, target 20 episodes

AI: OK, creating pipeline pipeline_20260305160000
    Theme: Cultivation boy
    Target: 20 episodes
    Style: Realistic cinematic
    
    Status: Initialized, ready to generate episode 1

Step 2: Generate Episode

AI calls start_generation(pipeline_id) to get generation prompt, then generates episode content based on the prompt.

Step 3: Submit AI Review

AI calls submit_episode(pipeline_id, episode, content) to submit generated content, then executes AI review.

Step 4: Process Review Result

AI calls process_ai_review(pipeline_id, episode, ai_result, content) to process review results.

If review fails (score < 7), automatically retry (max 3 times).

Step 5: Wait User Confirmation

After review passes, display preview and wait for user confirmation:

text

📋 Episode 1 Preview
━━━━━━━━━━━━━━━━━━━━━━━━
【Cultivation Journey Begins】

Young Li Yun discovers a mysterious jade pendant in the mountains,
从此踏上修仙之路...

✅ AI Score: 9.0/10
✅ New Hook: H-001 Origin of mysterious jade pendant

━━━━━━━━━━━━━━━━━━━━━━━━

Please select:
1️⃣ Approved, continue to next episode
2️⃣ Needs modification (please specify)
3️⃣ Pause
4️⃣ End

Step 6: Process User Confirmation

After user confirms, AI calls user_confirm(pipeline_id, action, note):

approve: Store graph, prepare next episode
modify: Regenerate based on feedback
pause: Pause pipeline
end: End pipeline

Step 7: Loop Generation

Repeat steps 2-6 until target episodes reached or user ends.

API Reference

Create Pipeline

python

create_pipeline(theme: str, target_episodes: int, style: str = "realistic cinematic")
# Returns: {"success": True, "pipeline_id": "...", "message": "..."}

Start Generation

python

start_generation(pipeline_id: str)
# Returns: {"success": True, "episode": N, "prompt": "generation prompt"}

Submit Episode

python

submit_episode(pipeline_id: str, episode: int, content: str)
# Returns: {"success": True, "review_prompt": "review prompt"}

Process AI Review

python

process_ai_review(pipeline_id: str, episode: int, ai_result: str, content: str)
# Returns: {"success": True, "passed": True/False, ...}

User Confirm

python

user_confirm(pipeline_id: str, action: str, note: str = None)
# action: "approve" / "modify" / "pause" / "end"
# Returns: {"success": True, "status": "...", ...}

Get Status

python

get_status(pipeline_id: str)
# Returns: Current pipeline status info

List Pipelines

python

list_pipelines()
# Returns: List of all pipelines

Resume Pipeline

python

resume_pipeline(pipeline_id: str)
# Returns: Resume result

Example Dialogue

text

User: Start a new pipeline, theme: Cultivation boy, target 20 episodes

AI: OK, creating pipeline pipeline_20260305160000
    Generating episode 1...
    
    📋 Episode 1 Preview
    ━━━━━━━━━━━━━━━━━━
    【Cultivation Journey Begins】
    Young Li Yun discovers a mysterious jade pendant in the mountains...
    
    ✅ AI Score: 9.0/10
    ✅ New Hook: H-001 Origin of mysterious jade pendant
    
    Please confirm: Approve/Modify/Pause/End
    
User: Approved

AI: Storing graph...
    Starting generation of episode 2...

Important Notes

Retry Mechanism: Max 3 retries when AI review fails
State Persistence: All states saved in data/pipeline_state.json
Graph Storage: Stored via remote API, requires network connection
Pause/Resume: Can resume via resume_pipeline after pause
Multiple Pipelines: Supports running multiple different-themed pipelines simultaneously

Story generation pipeline skill

Install

Story Generation Pipeline Skill

Features

Core Workflow

Usage

Start New Pipeline

Continue Pipeline

User Confirmation Actions

Dual Confirmation Control Mechanism

Layer 1: AI Quality Check

Layer 2: Human Confirmation

Graph Management

Graph Query

Graph Storage

State Management

State File: data/pipeline_state.json

Status Types

Script Description

pipeline.py - Main Control Loop

ai_reviewer.py - AI Quality Check

episode_generator.py - Episode Generation

graph_manager.py - Graph Management

API Description

Graph API

Episode Generation Logic

First Episode Generation

Subsequent Episode Generation

Finale Generation

Important Notes

Complete Workflow

Step 1: Create Pipeline

Step 2: Generate Episode

Step 3: Submit AI Review

Step 4: Process Review Result

Step 5: Wait User Confirmation

Step 6: Process User Confirmation

Step 7: Loop Generation

API Reference

Create Pipeline

Start Generation

Submit Episode

Process AI Review

User Confirm

Get Status

List Pipelines

Resume Pipeline

Example Dialogue

Important Notes

Related skills

State File: `data/pipeline_state.json`